Difference between revisions of "2013 Winter Project Week:MABS"

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* Polina Golland, MIT
 
* Polina Golland, MIT
  
SUMMARY HERE
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MABS is a program for multi-atlas based segmentation.  It uses a database of multiple, segmented
 +
input images to produce a segmented result on a new image.  The database is first "trained"
 +
to improve both accuracy and speed.  Then, when given a new case, examples are selected from the atlas,
 +
registered to the new case, and then voting is performed to create an output segmentation.
  
 
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<h3>Objective</h3>
 
<h3>Objective</h3>
* Objective 1
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* Create command line module for multi-atlas based segmentation
* Objective 2
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* If time allows, begin working on loadable module
* etc.
 
 
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<h3>Approach, Plan</h3>
 
<h3>Approach, Plan</h3>
PLAN HERE
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* A command line module was started in Summer project week, but it is not complete
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* It needs a way to specify the atlas and training directories, and specify output
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* To start with, we will export as Slicer labelmap, then move to RTSTRUCT after converting to loadable
 
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<h3>Progress</h3>
 
<h3>Progress</h3>
* Progress here
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* First results!
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* Segmented the brainstem using an atlas of two subjects.
 
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Latest revision as of 01:04, 11 January 2013

Home < 2013 Winter Project Week:MABS

Key Investigators

  • Greg Sharp, Nadya Shusharina, MGH
  • Polina Golland, MIT

MABS is a program for multi-atlas based segmentation. It uses a database of multiple, segmented input images to produce a segmented result on a new image. The database is first "trained" to improve both accuracy and speed. Then, when given a new case, examples are selected from the atlas, registered to the new case, and then voting is performed to create an output segmentation.

Objective

  • Create command line module for multi-atlas based segmentation
  • If time allows, begin working on loadable module

Approach, Plan

  • A command line module was started in Summer project week, but it is not complete
  • It needs a way to specify the atlas and training directories, and specify output
  • To start with, we will export as Slicer labelmap, then move to RTSTRUCT after converting to loadable

Progress

  • First results!
  • Segmented the brainstem using an atlas of two subjects.